Ideas are easy. Operationalization is everything.

May 20, 2026

A follow-up AI envisioning workshop made one point clear: success is not about the number of ideas, but about turning them into robust, business-ready use cases.

I write about this because many organizations are at exactly this point right now: moving from inspiration to execution. The critical shift happens in business design, not in technology selection.

Historic building reflected in a water canal under a clear sky, symbolizing focus and structured workshop work.
Historic building reflected in a water canal under a clear sky, symbolizing focus and structured workshop work.

Ideas are generated quickly. Value appears only when an idea becomes a clearly defined and executable use case.

Workshop location at the water canal with calm reflection

The location matched the objective: create clarity before technology decisions are made.

About four weeks earlier, we had the first session. That workshop focused on basics: What can agents actually do? How do they affect processes? Where does measurable value emerge?

We collected more than 50 ideas and roughly prioritized them. A strong start. But ideas without a plan and concrete actions remain potential on paper.

Follow-up on site: sharpen the business view before the technical stack

In the follow-up workshop, we deliberately stayed in the business domain. Questions included:

  • What should be achieved in concrete terms?
  • Who exactly is the target group?
  • What is the trigger?
  • What are input and output?
  • What is in scope, and what is explicitly out of scope?
  • How large should an agent be: one larger agent or several smaller ones?

We selected two use cases and worked through them in plenary with 20-25 participants. That was the turning point: broad debate, different perspectives, and ultimately better outcomes than isolated thinking.

What surfaced in parallel

The discussion quickly widened:

  • What happens when agents take over more and more logic?
  • Will classic low-code approaches still be enough in the future?
  • Should high-code options, for example with Azure Foundry, be considered from day one?

This reflects where many organizations currently are: right in the middle of orientation.

Three points from the closing discussion

  1. AI is a journey, and the train is already moving fast. The challenge is to bring the organization along and create an environment where experimentation is possible without creating chaos.
  2. It requires much more conceptual pre-work than expected. Ideas emerge quickly. Making them concrete enough for implementation is real work. That can happen in parallel with adoption.
  3. Without a clear IT strategy, building a sustainable AI strategy is difficult. Questions around best-of-breed, vendor strategy, scalability, security, cost control, and adoption come up inevitably.

One question came up repeatedly: Are other companies going through the same discussions? The honest answer is yes. These exact conversations are happening in many places right now.

Sign at the workshop room: AI Agents Workshop

Operationalization does not start with a prompt. It starts with shared understanding of goal, scope, and impact.

My conclusion: Organizational and legal framing is the foundation. Ideas are plentiful in every environment. What matters is the capability to turn ideas into robust, implementable use cases - business first, technology second.

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